**Sequence of Return Risk**,**Sequence of Return Risk**,- and let’s not forget that pesky
**Sequence of Return Risk**!

Huh? Isn’t that lame? Surely, **low average returns** throughout retirement ought to be included in that list, right? Or even top that list, right? That’s what I thought, too. Until I looked at the data! Let’s get rolling and look at some more SRR fun facts.

To see how much or how little average returns impact SWRs, let’s look at the following example of a retiree with a 30-year horizon and an 80/20 equity bond portfolio. I calculate the SWRs with the following assumptions:

- All simulations are in real terms (CPI-adjusted withdrawals and CPI-adjusted asset returns)
- Capital depletion (final value =$0). Results would be qualitatively similar results if I use capital preservation, which would be more applicable for early retirees with a longer than a 30-year horizon.

As a warm-up, let’s look at the table below: three case studies for different retirement starting dates. It displays the SWR that would have exactly exhausted the portfolio over 30 years, the 30-year average return of an 80/20 portfolio (0-30 years, point to point CAGR), as well as the average returns over the 5-year windows: 0-5 years, 5-10 years, … 25-30 years.

Retiring in December 1968 would have afforded you an SWR of only 3.8%. And that would have exhausted your capital over 30 years! But the average return over the 1968-1998 period would have been a staggering 6.16%. The reason why you still ran out of money after 30 years is that you had low returns early on and the strong returns, even double-digit real returns in years 15-30, came too late.

If you had retired only ten years later you would have experienced a very similar 30-year average return: 6.03%. But the SWR would have been a staggering 9.12%. The strong returns came during the first 20 years of the simulation and the weak returns during the last 10 years that cover the recessions in 2001 and 2008/9 wouldn’t hurt your SWR anymore. Also, October 1955 is an intriguing case study: Only very underwhelming average returns: 3.45% over the next 30 years, but a very healthy SWR of 5.72%.

Of course, with case studies, we can go only so far. In the chart below, let’s plot the entire SWR and average return time series. Wow, the SWR and the average return are only very slightly correlated. Even if you knew the average return of your portfolio mix over the next 30 years, you’d have a hard time pinning down an appropriate SWR. Some of the lowest 30-year returns in the late 1800 and early 1900s actually coincide with relatively decent SWRs of around 4% and as high as 7%!

Very interesting! There have been plenty of examples where the 30-year SWR far exceeded the 30-year rate of return. **SRR is a risk that can go both ways**; sometimes it helps the retiree sometimes it hurts the retiree. We knew that already from last time: the beneficiaries and losers are the savers and retirees. If the retiree benefits then the saver loses and vice versa. It’s a zero-sum game!

Let’s do some more sophisticated statistical analysis. We run two linear regressions to “predict” the SWR based on future returns. 1) knowing only the 30-year average return and 2) knowing the average returns during the six windows: 0-5 years, … , 25-30 years. Of course, “predicting” the SWR is a bit of a misnomer. Nobody *knows* the future returns. This is more of a thought experiment of how well you could have pinned down the SWR if you had known future returns. Or, let’s call it *accounting* for the SWR in hindsight, rather than *predicting* it.

The results are in the table below:

- Knowing only the average returns over 30 years we get a pretty underwhelming regression fit. An R^2 of only 0.31, so knowing the 30-year return explains only 31% of the variance in the realized SWR. We already saw the poor fit/correlation from the chart above, but this is the statistical and quantitative confirmation. But note that the slope coefficient on the average return is positive and statistically significant. And for statistics wonks, yes, this is a Newey-West adjusted t-stat to account for the
*overlapping windows*. - Knowing the returns in the 6 separate windows you get an almost perfect fit: close to 96% of the variation in the SWR are explained by the average returns in the 6 windows. What’s more, the slope coefficients for the different windows are very different and all extremely highly statistically significant. They may sum up to roughly the same number as in the univariate regression, but the earlier windows get a much larger slope coefficient. By weighting the 6 different time windows differently we now get an almost perfect fit. Precisely what I mean by
**SRR matters more than average returns**: 31% of the fit is explained by the average return, an additional 64% is explained by the**sequence of returns**!

What’s even worse than getting screwed over by SRR in retirement? Very simple: first you get screwed over by SRR while saving and then again while withdrawing money in retirement. Let’s look at the following hypothetical retirement saver who starts saving $5,000 in 1959 and does so for 15 years. Then he withdraws $4,000 from the portfolio during retirement. During the last few years of the accumulation and the first few years of retirement, the 1973/4 recession hits. You get hammered twice because that’s exactly the kind of return profile that you want to avoid while saving (high return early on, low returns later) and retiring (low returns early on, high returns later).

To see how much this saver/retirement cohort lost from SRR let’s plot the actual portfolio value that’s subject to SRR and the hypothetical portfolio value had this person experienced the exact average monthly return that prevailed during those 30 years (orange line). Without SRR you would have about 25% more in your portfolio at the beginning of retirement. After 15 years of retirement, you would have seriously depleted your portfolio. Without SRR you’d be about 100% better off! So, SRR hurt you both while saving and during retirement. Bummer!

Last week after posting the first part of the SRR blog post, two commenters had suggestions on how to overcome or at least alleviate the SRR problem. Both of them are brilliant ideas. But only one of them works.

Instead of withdrawing a **fixed** amount regularly, why not withdraw a certain **percentage** of the principal. This can be a constant percentage or the age-dependent withdrawal percentage in the VPW rule. Now, the final net worth looks like it’s independent of the order of returns:

(1-w) ∙ (1+r1) ∙ (1-w) ∙ (1+r2) = (1-w) ∙ (1+r2) ∙ (1-w) ∙ (1+r1)

Since the final net worth is the same, does that mean SRR is irrelevant for people who apply the VPW? Not really. Because the second withdrawal will now differ depending on which of the returns is larger. Imagine r1>r2. Then your second withdrawal is higher when you experience r1 first than when you experience r2 initially. So, you can’t hide from SRR. If you try to equalize the final portfolio value through VPW then SRR hits you through the withdrawal amounts! If you try to equalize the withdrawal amounts then SRR hits you in the final portfolio value. Pick your poison! The VPW has its pros (and cons) as we showed here, but it can’t eliminate SRR!

For retirement savers there is one sure-fire way to avoid missing out on strong equity returns early during the accumulation phase: Borrow against your future retirement account contributions and invest the whole loot as one big **lump-sum payment** without further contributions in the future (i.e., use your future retirement contributions to pay down the margin loan). Sounds crazy? Two researchers from Yale found that this is a way to “diversify across time,” which is just another way of reducing SRR. As we showed last week, a lump-sum investment is not subject to SRR!

If this sounds too extreme to you, I’d have to agree. There are multiple reasons why this is not workable. For example, since I work in a very volatile industry I’d not be comfortable borrowing against future earnings. But there are ways to at least alleviate the SRR problem:

- Hold a 100% equity portfolio early on. Don’t bother about holding any bonds.
- Don’t bother about paying down low-interest debt when young (mortgage, low-interest student loans). Put every last dollar you can scrape together into the stock market early on. (of course, high-interest debt, especially debt with interest higher than your expected equity return should be paid down as early as possible)
- Once you have a critical mass of equity investments, then tackle your low-interest debt.

The benefit of this method is twofold: 1) you gain from the higher expected return in equities over fixed income investments and 2) you alleviate the SRR by spreading around the equity risk more evenly across time. It’s a win-win!

- Part 1: Introduction
- Part 2: Some more research on
**capital preservation vs. capital depletion** - Part 3: Safe withdrawal rates in different
**equity valuation**regimes - Part 4: The impact of
**Social Security benefits** - Part 5: Changing the
**Cost-of-Living Adjustment**(COLA) assumptions - Part 6: A case study: 2000-2016
- Part 7: A
**DIY withdrawal rate toolbox**(via Google Sheets) - Part 8: A
**Technical appendix** - Part 9:
**Dynamic**withdrawal rates (Guyton-Klinger) - Part 10: Debunking Guyton-Klinger some more
- Part 11: Six criteria to grade dynamic withdrawal rules
- Part 12: Six reasons to be suspicious about the “
**Cash Cushion**“ - Part 13: Dynamic Stock-Bond Allocation through
**Prime Harvesting** - Part 14: Sequence of Return Risk
- Part 15: More Thoughts on Sequence of Return Risk

]]>

Besides, in case you haven’t heard it, yours truly, Big Ern, was asked by Jonathan and Brad at ChooseFI to be an occasional contributor to their awesome Financial Independence podcast. Specifically, I’ll be the in-house expert on everything related to safe withdrawal rates. And that’s alongside an A-plus-rated team of experts: real estate guru Coach Carson, tax expert The Wealthy Accountant, and business guru Alan Donegan from PopUp Business School! How awesome is that? Because Sequence of Return Risk is something we’ll cover in the podcast soon as part of a crowdsourced case study, I thought it would be a good time to have a go-to reference post on the topic here on our blog. So, once again, make sure you head over to the ChooseFI podcast:

Investopedia has a nice definition:

“[s]equence-of-returns risk is the risk of receiving lower or negative returns early in a period when withdrawals are made from an individual’s underlying investments. The order or the sequence of investment returns is a primary concern for retirees who are living off the income and capital of their investments.”

In other words, if you are a buy-and-hold investor your final asset value is simply a function of the compound (geometric) **average** growth rate. It doesn’t matter in what order the returns came in because of the beautiful fundamental rule of mathematics: (1+x)(1+y)=(1+y)(1+x). All that arithmetic goes out the window, however, if you have additional cash flows into or out of the portfolio over time. Let’s look at a little example, see the table below. For a buy and hold investor it doesn’t matter if you get two consecutive 10% returns, or -15.00% followed by +42.35%, or +42.35% followed by -15%. They all generate a compound return of exactly +21% and the same final portfolio value of $121 for each initial $100 invested. The IRR (internal rate of return) is always 10% p.a.:

A retiree, however, who withdraws $10 per year (assuming the withdrawal occurs at the beginning of each year) will not be indifferent. The final portfolio value and IRR now vary depending on the sequence of returns. If you suffer a 15% loss early on you end up with less money than with steady 10% returns. The intuition is straightforward: Because you withdraw money at the bottom of the market, you experience the +42% return in a portfolio that’s already significantly reduced. You have a lower IRR because you participate less in that strong +42% return. In contrast, receiving a high return early on will ensure that you handily beat the +10%/+10% scenario.

Huh? Why would savers be impacted by SRR? Isn’t this something that only affects retirees? No! SRR impacts **all** investors who have cash flows out of the portfolio and/or into the portfolio. Let’s look again at the 2-period example above and add a third person, a **saver** who starts out with $0 and then invests $10 per year at the beginning of each year.

Among the three different return scenarios, the saver would greatly appreciate the -15%/+42% return pattern, see table below. The highest final value occurs when returns are low initially and then stronger in the second period. The exact opposite as for the retiree. Also look at the IRR: close to 20%, which is almost twice the IRR of the “Buy and Hold” investor. Makes perfect sense because we suffer less from the market drop early on with less money exposed to the big drop. But then we benefit from the large increase with all the principal invested. Sweet!

Also, notice something peculiar about the final portfolio values: The retiree and saver portfolio values add up to the Buy and Hold portfolio values: For example, for the +42%/-15% case: $100.40 + $20.60 = $121.00. This is not a coincidence. The cash flows of the saver and retiree add up to exactly the Buy and Hold strategy. This explains that when the retiree’s IRR lags behind the Buy and Hold Strategy, the saver’s IRR must beat the buy and hold IRR. Sequence of return risk means that there is a **zero-sum game between savers and retirees!** During periods when the retirees suffer from SRR, savers will benefit and boost their IRRs and it’s all thanks to SRR!

Yes, you heard that right. The ERN family has **benefited** from SRR over the last decade or so. You can probably already see where we are going with this, so let’s do the following more thorough calculation. Let’s look at monthly real equity returns from our SWR study database and simulate 10-year rolling windows of three investors:

**Buy and Hold**for 10 years**Retiree:**Start with the same initial wealth as investor 1, but withdraw at a 4% p.a. initial rate and then increase the withdrawals by the rate of inflation (the standard 4% Rule)**Saver:**Start with $0 initial wealth but save the exact same amount that investor 2 withdraws.

Clearly, we have a zero-sum situation again: The cash flows of investors 2 and 3 add up to the buy and hold strategy because the savings and withdrawals exactly cancel out each other.

Now, let’s calculate the IRR of the 3 investors over time, see plot below. Each value plotted corresponds to the end point of a 10-year window and refers to the Buy and Hold, Retiree, and Saver IRR, respectively. It turns out that over the last 10 years (3/2007-3/2017) the IRR for the 3 investors were: 5.65% for Buy and Hold, 4.46% for the Retiree, and 10.48% for the saver. In fact, throughout much of the 2000s, the savers did better than the buy and hold investors (the green line is mostly above the blue since 2010). And the explanation is very simple: Retirees got hammered by SRR during the 2000s, compliments of two nasty drawdowns. We benefitted from the two bear markets because our cash flows were largely the mirror image of the retirees. Specifically, Big Ern started with about $0 in the year 2000 and built up the ERN family portfolio through steady contributions to retirement plans and taxable savings. Picking up stocks at bargain basement prices actually increased our IRR to levels way above the Buy and Hold IRR.

Another way to look at the same image to better bring out the zero-sum game feature: Subtract the IRR of the Buy and Hold (the blue line) from the retiree and saver IRR, i.e., calculate the *incremental* IRR above the Buy and Hold investor, see chart below:

**Side note:** The zero-sum feature applies only to the cash flows. The incremental IRRs don’t sum to zero* for (at least) two reasons: 1) the IRR calculation is a highly non-linear affair, and 2) in this example, the saver has less money invested, on average, which explains why the magnitude of the excess IRR of the saver is much higher than that of the retiree. But you can show that the incremental IRRs will always have opposite signs.*

Needless to say, occasionally, the saver will get hammered, too! For the 10-year windows that started between 1993 and 1995 and ended between 2003 and 2005, the situation is reversed: The retiree experienced the very strong returns early during the 10-year window. The saver, in contrast, participated to a much lower degree in the late-1990s equity rally but then got slammed in the 2001-2003 bear market, right when he/she had the maximum portfolio value. Murphy’s Law! That’s the dip in the green line in the early 2000s.

Just for fun, here’s also the longer time series, starting in 1900. The +5% outperformance for the saver over of the most recent 10-year window seems impressive but it’s not the highest in history. The 10-year window that ended in late 1939, of course, was even better for savers: they benefited from the steep drop in equities during 1929 and the early 1930s! Of course, in the window that started just a few years later (1932-1942) the result is reversed: As a saver you do significantly worse than the Buy and Hold investor because of the strong recovery from the stock market trough.

One more cool plot I created: In the chart below, let’s look at how the equity market performs over the 10 years when the saver IRR either significantly beats the Buy and Hold strategy (blue bars), is about in line with the Buy and Hold strategy (green bars) and significantly lags behind the Buy and Hold strategy (maroon bars). As expected, the profile of equity returns is increasing over the 10-year window when the saver benefits from SRR. But that exactly the return profile when the retiree loses the most!

One more thing occurred to me: Before doing this research, it would be easy for us to believe that in retirement we don’t have to worry about a bear market because we did quite well with our portfolio during the accumulation phase between 2000 and 2017. Despite all that market turmoil! You read this quite often in the FIRE blog community! But that’s a delusion: the retirees’ losses during that time were our gains due to the zero-sum feature we pointed out here:

**The fact that we did well during 2000-2017 should actually worry us more about volatility in retirement, not less.**

In any case, we have so much more material on SRR! I don’t want to go above 3,000 words in one post and it wouldn’t be fair to leave out the other fun content we still have on this topic. So, stay tuned for a part 2 next week!

Sequence of return risk is a symmetric risk: you can benefit from it or it can seriously harm your investment returns. It impacts both retirees and savers and the risk is exactly a zero-sum game. Sometimes the retiree loses and the saver gains, as in the 2000s, but there were many instances where this was reversed.

- Part 1: Introduction
- Part 2: Some more research on
**capital preservation vs. capital depletion** - Part 3: Safe withdrawal rates in different
**equity valuation**regimes - Part 4: The impact of
**Social Security benefits** - Part 5: Changing the
**Cost-of-Living Adjustment**(COLA) assumptions - Part 6: A case study: 2000-2016
- Part 7: A
**DIY withdrawal rate toolbox**(via Google Sheets) - Part 8: A
**Technical appendix** - Part 9:
**Dynamic**withdrawal rates (Guyton-Klinger) - Part 10: Debunking Guyton-Klinger some more
- Part 11: Six criteria to grade dynamic withdrawal rules
- Part 12: Six reasons to be suspicious about the “
**Cash Cushion**“ - Part 13: Dynamic Stock-Bond Allocation through
**Prime Harvesting** - Part 14: Sequence of Return Risk
- Part 15: More Thoughts on Sequence of Return Risk

]]>

End of story! End of story? Not so fast! Even if you’re familiar with the subject already, please keep reading because we’ll have a **new spin** on this old topic. Spoiler alert: we propose a way dollar cost averaging will reduce risk and have the same average return as the lump-sum investment!

As Wikipedia explains it:

*“By dividing the total sum to be invested in the market […] into equal amounts put into the market at regular intervals […], DCA hopes to reduce the risk of incurring a substantial loss resulting from investing the entire “lump sum” just before a fall in the market.*

So, instead of investing a large lump sum, say $10,000 all in month 1, we could alternatively spread the investment over 2 months ($5,000 each), over 3 months ($3,333.33 each) or over 4 months ($2,500 each). The total investments are the same but DCA could potentially spread out the risk of investing one large amount all in one month.

* Side note 1: There is some confusion about the meaning of DCA. The regular monthly investments of a fixed dollar amount (into a 401(k) plan, for example) over many years will imply that when the market is down you buy more shares, and when the market is up you buy fewer shares. Some people call this dollar cost averaging as well. But the periodic investments into a 401(k) plan are more or less mandatory; ten years ago I couldn’t have funded my 401(k) with a lump sum of ten years’ worth of contributions. Dollar Cost Averaging in the context of today’s post means having the funds available and voluntarily *spreading

**Side note 2:** Speaking of 401(k) accounts, some personal finance bloggers advocate **“front loading”** your retirement account contributions, i.e., investing a big chunk or potentially all of your maximum annual 401(k) contribution in January. Physician on FIRE and MadFIentist had blog posts on this recently. The rationale is the same as with lump sum vs. DCA: Since the equity market goes up on average you want to have the maximum equity exposure as early as possible. But keep in mind that the regular periodic 401(k) contributions are not really the same as DCA because your investments occur when you get your income. In contrast, DCA means you **voluntarily** delay investing while holding on to cash, waiting to deploy the investments over time.

To see whether lump sum investments beat DCA, let’s run some simulations. We use monthly equity returns (S&P500 total return) since January 1871 minus a short-term, risk-free return (3-month T-Bill after 1926, 1-year T-bill before 1926, due to data availability). We calculate how a lump sum investment would have performed over 12-month windows relative to spreading out the investment. Vanguard’s study uses DCA spread out over 12 months and then also performs the same analysis over 6, 18, 24, 30 and 36 months, but we are more interested in shorter DCA horizons and use 2, 3, 4, 5, 6, 8, 10, and 12 months instead. Below are the results for the entire sample since 1871 and also for the more recent period since 1980.

We pretty much replicate the results from the Vanguard study: DCA indeed reduces risk but lags behind the lump sum investment in every other conceivable measure: returns are lower and Sharpe Ratios (excess return divided by risk, i.e., a measure of risk-adjusted mean return) are lower. Over the earlier period, there were a few DCA simulations that yielded marginally higher probabilities of positive returns, but that’s been reversed since 1980. Also, DCA’s probability of beating the lump sum investment is always below 50% and it declines the more we spread out the investments. Bummer!

So we confirmed the well-known result for all DCA horizons between 2 and 12 months: The peace of mind of investing in several installments over time comes at a high price. Some would argue that Dollar Cost Averaging is only for jittery chicken-little investors. But in the FIRE community, we are all cool and rational investors so there is no place for Dollar Cost Averaging around here, right? **Or, maybe there is?! **

If the risk reduction in DCA is for real but the opportunity cost messes up our returns, why not simply spread out the investments to reduce risk, but start investing **before** the windfall arrives. Could that be the best of both worlds? Avoid the opportunity cost and still get the risk reduction, see below!

I try the DCA over 3 months starting 1 month before the windfall and the DCA over 5 months starting 2 months before the windfall, see the chart above. Notice the beauty of this assumption: We now invest 1/3 of the equity portfolio for 11, 12 and 13 months each. So the average length of the equity investment is indeed 12 months, the same as in the lump sum case! And analogously, invest one-fifth for 10, 11, 12, 13 and 14 months, also for an average of 12 months.

As the baseline, let’s assume that we are able to borrow the funds prior to the windfall date at the risk-free rate. That might be a bit of a stretch, but for folks who have an emergency fund, why not just “borrow” from that account for one or two months? The opportunity cost is exactly the risk-free rate! And what if a big expense shows up just during that one or two-month window? Come on, everybody, be creative. Use the credit card float or put the charge on a new card with introductory zero percent interest. I don’t have to tell you how to hack that, right?

Of course, as many of you may know, we don’t even have an emergency fund. But we could access a Home Equity Line of Credit (HELOC) to borrow the funds, though at a higher interest rate; the “Prime Rate” in our case (roughly the risk-free rate plus 3% p.a.). So, let’s assume that when borrowing the pre-windfall investment we have to pay that higher interest. But likewise, we also use the excess cash we have when the windfall arrives to pay down our existing HELOC balance (normally around $20,000-$25,000) until we’re done with the DCA. So, how would we implement a DCA of a $10,000 investment over 5 months with an assumed $20,000 initial HELOC balance?

- 2 months before windfall, borrow $2,000 from HELOC to invest. Balance $22,000
- 1 month before windfall, borrow $2,000 from HELOC to invest. Balance $24,000
- Windfall: Receive $10,000, invest $2,000 and use the remaining $8,000 to pay down the HELOC. New Balance: $16,000
- 1 month after the windfall: Take $2,000 out of HELOC and invest. Balance: $18,000
- 2 months after the windfall: Take $2,000 out of HELOC and invest. Balance: $20,000

This scheme generates an **average** HELOC balance of exactly $20,000, no different than our “normal” HELOC balance. So, don’t be surprised if even with borrowing costs the DCA results will look very similar to the baseline!

If you have no sizable emergency fund and no HELOC either you could still buy equities on margin at an extremely low cost: **equity index futures** deliver exactly what we want: the index total return (incl. dividends) minus risk-free rate. See our other posts on futures trading: general info here and the post on the Synthetic Roth IRA. Unfortunately, futures contracts are also very lumpy: One single S&P500 futures contract is worth 50x the index level, currently just under $120,000. You’d need a really nice size inheritance to make it worthwhile implementing DCA with equity index futures. Better be nice to your Aunt Betty!

In any case, here are the simulation results, see table below:

- There is essentially no difference in average returns between the lump sum investment and the DCA. That’s not a surprise because the average investment length in the equity market is now the same for both the lump sum and the DCA.
- Amazingly, there is no sizable deterioration in the average return even when factoring in borrowing costs. But again, that’s due to having an existing HELOC balance. The borrowing cost before the windfall is exactly offset by using some of the windfall money to temporarily pay down the HELOC until the conclusion of the DCA.
- The Sharpe Ratio under DCA is higher than with the lump sum. You get a higher probability of positive returns than with the lump sum investment and there is higher than 50% chance of beating the lump sum investment with DCA.
**How cool is that?!**

Of course, the DCA with borrowing will not be feasible all the time. Here are some important limitations:

**Uncertainty about the timing of the windfall:**If we don’t even know if or when the windfall arrives it might not be so prudent to put borrowed money in the stock market!**Borrowing limits:**If you have a net worth of $1,000,000 and the windfall is $30,000 you’ll likely find it easy to come up with $10,000 for one month before the windfall actually arrives. If it’s the other way around and you expect a $1,000,000 windfall and your current net worth is only $30,000 you will probably not get a $300k+ loan to invest the month before the windfall!**Legal and tax constraints:**If you want to invest a lump sum in a retirement account for a specific calendar year you can do that as early as January of that year. But you can’t invest the 2018 contribution before January 1, 2018, at least not in the retirement account. Back to the Front Loading technique mentioned above: Investing one large lump sum in January might be advantageous to the periodic investments. Investing three equal amounts in December, January and February (or five equal amounts in November-March) might be even more advantageous but it’s not allowed in the retirement account because of restrictions on how much you can invest in each calendar year.

We are getting beyond 2,000 words so I don’t want to push this too much more. But the superior performance of DCA with borrowing vis-a-vis the lump sum investing is not a fluke. Quite the opposite, in addition to the empirical evidence, I can **prove this mathematically**. It has to do with the fact that returns and risk in a multi-period investment problem are aggregated very differently. You don’t aggregate risk linearly.

Here’s a simple example **(please skip if you don’t like statistics and mathematics)**: Imagine there are three consecutive (monthly) returns X1, X2, X3. They have some joint distribution and all I require is that they have the same expected returns, the same variance/risk, but there could be some non-zero correlation between the returns.

**Lump sum investment:** If you invest a lump sum of $1 after X1 has been realized, you would be exposed to returns X2 and X3 only and the variance of the lump sum return is:

V_LumpSum = Var(X2) + Var(X3) + 2∙Cov(X2,X3)

The risk (=standard deviation) would be the square root of that.

**Dollar Cost Averaging:** If you invest $0.50 before X1 has been realized and another $0.50 before X3 has been realized, then this would be a form of DCA. You invest half the amount one month before the windfall and the other half in the month after the windfall. Slightly different from the 1/3, 1/3, 1/3 setup above but the intuition is the same. $0.50 would be exposed to X1 and X2 and $1.00 would be exposed to X3. The variance of the DCA portfolio return is:

V_DCA = 0.25∙Var(X1) + 0.25∙Var(X2) + Var(X3) + 0.5∙Cov(X1,X2) + Cov(X1,X3) + Cov(X2,X3)

Unless all returns are perfectly correlated, i.e., Cov(Xi,Xj) = Var(Xi) = Var(Xj), the DCA variance is smaller than the lump sum investment variance. That’s because with DCA you spread out the risk more evenly between X1 and X2. In the most basic case where the covariances are all zero (returns are uncorrelated, not a bad assumption for equity returns!), the lump sum investment has a variance that’s 1/3 higher than the DCA portfolio: 2.0∙Var(Xi) vs. 1.5∙Var(Xi). This translates into 15.5% higher risk in the lump sum investment! Despite having the same mean returns the two portfolios have very different risk profiles!

**Side note 1:** Yes, yes, yes, I know that returns are not additive but they compound. One would define the X=log(1+return) to fix that!

**Side note 2:** We clearly took today’s post from geeky to **super-geeky** with this, but there are some of us in the FIRE community who wouldn’t have it any other way!

Dollar Cost Averaging is getting a bad reputation. But before you ridicule the proponents of DCA, keep in mind that, if done properly, DCA delivers exactly what it promises: Risk reduction **without** the opportunity cost. It will not beat the average return but it delivers the same expected return with less risk. Of course, it involves a little bit of financial hacking. Specifically, it requires leverage (gasp!) and not everybody has an appetite for that. But we do! We wrote a post a while ago on the seven benefits of debt and leverage. And we might mark this one as benefit number eight: Use **leverage to reduce risk.** Who would have thought?

]]>

Research has shown that historically the stock market has done extremely well whenever the FOMC meets. Let’s look at some of the numbers. I gathered data since January 1990 and computed the weekly S&P500 returns. Specifically, I calculate weekly total returns (dividends included) and subtract a risk-free (very short-term T-bill rate calculated per week). Out of the 1,421 weeks, we had 218 weeks with FOMC meetings and 1,203 without. The results are in the table below:

- During FOMC weeks one would have gathered a staggering 27% annualized compound return, compared to only about 6.5% for the entire period. And that’s in excess of cash!
- The realized risk during FOMC weeks is slightly lower than during other weeks. Nice!
- Quite intriguingly, the compound return during FOMC weeks is higher than the arithmetic average return (26.77% vs. 24.88%). Normally it’s the other way around because it takes an 11.11% gain to recover from a 10% loss. The explanation is that during FOMC weeks, returns have
*positive*skewness. So, FOMC weeks offer the stock return “Holy Trinity”: High Return, Low Risk, Positive Skewness! Amazing! - Non-FOMC weeks have the opposite characteristics: They have lower returns than the average, higher risk and lower (more negative) skewness.
- Drilling down further into non-FOMC weeks, it appears that the pre-FOMC week and especially the post-FOMC weeks have weaker average returns. It must be that after the FOMC euphoria we suffer a bit of a hangover!

How would a portfolio have performed if we had been invested only during specific weeks (and held cash during the other weeks)? In the chart below, I plot the cumulative return of the S&P500 over all weeks (black line) and FOMC weeks and various non-FOMC weeks (mutually exclusive and exhaustive). Quite amazingly, we garnered the majority of equity returns simply during the 218 weeks with FOMC meetings. Pre-FOMC and post-FOMC are just flat lines and the “all others” weeks underperform the FOMC weeks even though there were 767 such weeks (3.5 the number of FOMC weeks). And it even gets better: during FOMC weeks you actually made money during the volatile 2001 or 2008/9 periods, while during the non-FOMC weeks you were exposed to all the nasty volatility during the recessions. How amazing is that?

OK, I admit I’m not the first to find this effect. This FOMC effect has been pretty well-known in finance circles for a while. For example, researchers at the New York Fed have drilled down even more into this FOMC effect and looked at daily and even intra-day data. They found that the roughly 0.5% average return per FOMC week is mostly due to the actual FOMC day and the days right before and after. Quite intriguingly, the excess return happens mostly **before (!)** the FOMC announcement!

**Update (5/4/2017): Murphy’s Law of blogging struck again! The S&P500 was actually down on the FOMC decision day (Wednesday, 5/3). But weekly return still has hope to come in above zero, so stay tuned!!!**

**Coincidence?**Could this just be a fluke? Not likely. The outperformance of this FOMC drift is statistically significant. I ran some tests on the weekly numbers above to confirm that, and the NY Fed wrote a whole detailed 63-page research paper and found that this effect is highly statistically significant.**Higher risk = higher return?**Not likely! First of all, the**realized**risk during the FOMC week is actually lower, see our table above. It is true, though, that the**implied**volatility index (VIX) is marginally higher before the FOMC meeting. But that small difference would not justify the outsized excess returns during the FOMC week.**Relief Rally?**One theory I had was that before each FOMC meeting there is a small probability of a black swan event; everybody has the concern that the FOMC could “blow up the economy” with a policy mistake. When that doesn’t happen a relief rally ensues. But that theory is negated by the FOMC drift**before**the announcement according to the NY Fed study. Unless, of course, and now we have to go to a full-blown conspiracy theory, somebody inside the meeting room leaks information to his/her Hedge Fund friends. True, there have been leaks before, but it would be unthinkable that this could go on unnoticed for decades.

**So, to be honest: There is no good explanation for this. ****If anyone has a good theory, please share below!**

If you are not intrigued by now, how about this: the FOMC effect works regardless of the policy decision of the FOMC. There are some slight differences depending on whether the FOMC raised rates, lowered rates or left the rate unchanged, but they don’t appear statistically significant. In fact, some of the best FOMC week returns occurred during the late 1990s (rate hikes) and 2013/14 (tapering), i.e., during monetary tightening.

Very easy: Load up on equity futures the Friday before the FOMC week, sell everything on the Friday after the FOMC! But I would strongly advise against actively trading this. This is now a well-known (though not well-understood) phenomenon. I wouldn’t be surprised if some hedge funds are already betting on this, which would eventually diminish this profit opportunity. What I can recommend, though, is to not be a sucker; if you intentionally or unintentionally bet **against** this phenomenon you’ll likely lose money. I have often caught myself wondering if I should derisk ahead of the FOMC meeting. Fight those lizard brain instincts! Our blogging friend Physician on FIRE had a nice post “Don’t just do something. Stand there!” on the topic of not overreacting to sudden market moves. For the FOMC weeks, it’s even easier not to overreact because the dates are known a year in advance. Tie your hands, tie yourself to the mast like Ulysses and resist the temptation to derisk. Especially this year there will be some uncertainty surrounding the FOMC meetings regarding the timing of additional rate hikes and the “balance sheet normalization.” So, I would follow the simple rules below:

- Don’t derisk ahead of the FOMC meeting for fear of market volatility. FOMC weeks are some of the best weeks for the stock market.
- If we have a large lump-sum to invest in stocks, we try to invest
**before**the FOMC meeting, if possible. - If we are taking out money from stocks, we try to wait until
**after**the FOMC meeting, if possible.

*Disclaimer: Please use common sense and consult a professional before making investment decisions. Also, read our general disclaimers!*

]]>

Add to that our series on safe withdrawal rates where we found that over a long retirement horizon bonds become much less attractive. In the Trinity Study with retirement horizons of 15-30 years, you can get away with a bond share as high as 50%. But over long horizons of 40-60 years in the FIRE community, the low expected returns of bonds can jeopardize the sustainability of the portfolio as we showed in part 2 of our series.

Has anything changed since last year? Are we now a bit more optimistic about bonds? After all, yields have risen. The 10-Year Treasury yield reached 2.6% earlier this year but has since fallen again to about 2.2-2.3% just last week.

**Let’s look at the numbers in more detail**

Wikipedia calls it “the process of allocating capital in a way that reduces the exposure to any one particular asset or risk”

Personally, and in this particular context, I would define it as “the reduction of portfolio risk due to allocating toward assets with less than perfect correlation”

There is a subtle difference between the two and we shall see the implications below.

Specifically, how much risk reduction through diversification do we get when we start at 100% stocks (not too far away from our current portfolio) and start mixing in bonds? Let’s look at the current financial market landscape. Our current (as of 4/21/2017) Return/Risk/Correlation assumptions over the next year are as follows:

- Equities: 7% p.a. return (nominal), 15% risk p.a.
*(to be perfectly honest, our personal expected return assumption is closer to 6% nominal, but 7% seems more in line with what most other investors are using)* - 10Y Treasury Bonds: 2.25% p.a. return (nominal), 6% risk p.a.
*(A big caveat: the expected bond return doesn’t have equal the yield. We will talk more about that later!!!)* - Risk-free asset: 1.35% p.a. return (1 year CD according to Bankrate.com as of 4/21/2017). (
*Note: Below I will call this “cash” out of habit, though, at this one-year horizon, obviously the 1-Year CD is the risk-free asset.)* - Stock/Bond correlation: -0.30, based on monthly correlations 2007-2017

How much return/risk can we expect when going from 100% equities to an 80/20 portfolio? Let’s look at the efficient frontier diagram. We plot the efficient frontier (blue line) and the 80/20 portfolio is right on that line (by definition) with an expected return of 6.05% and expected risk of around 11.70%. That’s a pretty nice reduction in risk: 11.70% instead of 15% in an all-equity portfolio. 3.3 percentage points.

*Side note: The backward-bending part of the Efficient Frontier, i.e., the lower part connecting “Bonds” with the 4.8%/3.2% dot, is normally not considered part of the efficient frontier.*

But is that reduction really due to diversification? See the green line we added to connect the Stock and Bond dots? That would have been the efficient frontier if stocks and bonds had a perfect correlation of +1.0. Would we call moving along that line really diversification? I would call that “derisking” instead. So, a big portion of the risk reduction is not exactly due to diversification, but rather due to the much lower risk level in bonds.

**Reduction in Risk = Effect from derisking + Effect from diversification**

In the chart below, it looks like 1.8% of the risk reduction is due to derisking and only 1.5% due to diversification.

In the distinction derisking vs. diversification, bonds become even less attractive when we do the derisking through cash (otherwise known as hedging). The line connecting Cash with Stocks is above Bond risk/return dot! And we can move along that line by simply mixing x% stocks with 100-x% cash, see below. With an 83.2% equity share and 16.8% cash allocation we could have attained the same expected return as the 80/20 S/B portfolio, but with a roughly 12.5% expected risk level. Out of the 3.3% risk reduction, 2.5% are simply due to **hedging out** some of the equity exposure. You get only an additional 0.8% from bonds.

I had this lengthy discussion with a reader about Derisking/Hedging vs. Diversification after our Great Bond Diversification Myth post. Taking the Wikipedia definition of diversification, one can certainly make the case that moving along the Stock-Cash line is indeed diversification. After all, we are reducing “exposure to one particular asset or risk” as Wikipedia puts it. But it’s still nonsensical to call that diversification. Ask yourself if someone told you that they found a way to diversify their portfolio to reduce risk by 20%. But all they did was sell 20% of all assets and put that money into cash. Would you call that diversification? No, it’s hedging/derisking. Would you be impressed? I certainly wouldn’t! It’s like someone suggested a new way of reducing my heating bill by 20%: move to a 20% smaller house.

Actually, talking about hedging, even the Wikipedia definition states:

*“Diversification is one of two general techniques for reducing investment risk. The other is hedging.”*

So, to the extent that hedging and diversification are mutually exclusive, simply reducing the equity exposure (=hedging) is not diversification, even by the Wikipedia definition!

I started writing this post last week and used 2.25% as the bond expected return because that was roughly the 10-year yield on Friday, April 21, 2017. Over the weekend, **Murphy’s Law of Blogging** struck again: Bond yields rallied in response to the French election, right after I finished the post but before today’s publication. I thought about changing all the charts to reflect the new reality. But in the end, I didn’t. This event shows that if bond returns continue their path towards normalization, i.e., higher yields over the next 12 months, the expected return for bonds should be adjusted downward. That raises an interesting question:

**How low would the bond expected return have to be to drive the bond diversification benefit to exactly zero? **

If we push the expected return of bonds to about 0.8%, then the efficient frontier just exactly “hugs” the Cash-Stock line, see chart below! 10-year Treasury bonds currently have a duration of 8.0, so a relatively modest increase of 0.18% in the bond yield over the next 12 month would do the trick: 2.25-0.18*8=0.81. 10-Year bond yields went up by 0.10% between the Friday close and Wednesday morning, so 0.18% isn’t that much in one year!

Actually, I checked at my Bloomberg terminal on Tuesday (4/25/2017) and the median forecast for the 10-year rate is 2.91% by Q1 of 2018. Most economists believe a much more rapid increase than 0.18% over the next year! There are many reasons investors expect a rise in interest rates:

- The Federal Reserve is raising short-term interest rates at a projected pace of 0.50%-0.75% p.a. While this doesn’t necessarily mean that all interest rates at all maturities have to go up in lockstep, the general trend for interest rates at all maturities will be up for the foreseeable future.
- The Federal Reserve is currently sitting on a large pile of excess Treasuries and MBS (mortgage-backed securities) as a result of its various quantitative easing (QE) programs in the past. Reducing that big pile of now unwanted investments to the tune of several trillions (with a “t”!!!) of dollars is uncharted territory and financial markets are worried, see Yahoo link here: “The Fed has a problem after the biggest bond-buying binge in history.”
- Stronger growth could be around the corner after business investment looks like it’s finally gaining momentum again.

But for full disclosure, there are also reasons to believe bond that yields could stagnate or go down again:

- Geopolitical risk: U.S. Treasury bonds remain the #1 safe haven asset.
- The U.S. economy could sputter again. The 2017-Q1 GDP numbers (released later this week on April 28) will likely look really weak due to consumers.

The reality is probably somewhere in between. A weighted average of the rising rate scenario and a small probability of the stagnant/lower rate scenario will still have a rising interest path. Still bad for bonds!

We also checked how much wiggle room other bond investments have, i.e., how much of a yield increase over the next 12 months they could sustain before they lose their diversification potential. Specifically, we looked at the following iShares bond ETFs: IEI (5-year U.S. Treasuries), TLT (20+ year Treasuries), LQD (corporate investment-grade bonds), HYG (high yield bonds). They have between 0.15% and 0.30% wiggle room before any and all diversification benefit is wiped out. Not a pretty picture!

Bonds offer some degree of diversification. But don’t get your hopes up too high. Even if you believe that bond yields will not change in the foreseeable future (good luck with that!), the diversification potential from bonds is not that impressive. What’s worse, even if bond yields go up by just a moderate 0.18% (actually by less than what most forecasters believe), a stock/bond portfolio has an even worse risk/return tradeoff than a stock/cash portfolio. Bonds would have to offer much higher yields before we get interested again! If the 10-year yield reaches 3% again, which is the long-term target for the Fed Funds Rate, see Fed projections here, I might take another look at bonds!

*As always, please check our disclaimers. If unsure, consult with a professional before making any investment decisions!*

]]>

*****************

A quick online search of student loan debt in America reveals the astonishing truth about the widespread, increasing expense of attending a college or university. Currently, more than 44 million borrowers have amassed over $1.4 trillion of student loan debt, and each year, the total continues to climb. While taking out student loans is now firmly embedded in the college experience for the majority of students, the picture remains bleak for borrowers. Here are five unfortunate facts about student loan debt in America to prove that point.

The Institute of College Access and Success reported that the average student loan debt undergraduate students leave college with is just around $30,000. The number has steadily increased over the last few years, up 4% from 2015, a rate higher than the average annual inflation or cost of living salary adjustments. Part of the problem aiding in the increased student debt burden faced by graduating students is linked to a decrease in state funding for public schools, resting at 18% lower than a decade ago and showing no signs of increasing in the near future. Graduates who select a standard repayment program spread over 10 years face a monthly payment of around $300, limiting their options for setting money aside for emergencies, establishing a retirement nest egg, or accumulating enough to contribute to the down payment for a home.

As reported in early 2017, the total outstanding student loan debt now surpasses credit card debt. The Federal Reserve Bank of New York published a report citing $779 billion in credit card debt held by all Americans, nearly half of the student loan debt burden. Although credit card debt can be more costly in terms of the interest rate charged by card issuers and banks, the payment terms carry far more flexibility than student loan repayment programs as well as lower minimum monthly payments on revolving balances. Neither debt burden is ideal, but the fact that student loans outpace credit card debt points to a clear problem facing younger generations of borrowers.

Although most statistics point to the student loan obligations of undergraduate borrowers, graduate and professional degree students are not immune to the crisis. Nearly 40% of student loan borrowers used the funding to finance a graduate-level degree or program, and when added to loans taken out for undergraduate studies, the total amounts due are hard to swallow. For an MBA student, the average student loan debt is $42,000, while a Master of Education graduate leaves school with just under $51,000. Law school students and medical school graduates have the most staggering average loan balances, currently at $140,000 and $161,000, respectively. Although graduate degrees often lead to higher paying jobs shortly after graduation, advanced degree students face a substantial debt obligation for an extended period of time.

In recent years, several repayment program alternatives have become available to certain borrowers, specifically those who are in low-salary jobs or public service positions. However, the addition of income-based repayment programs has not helped ease the potential for default among the millions of student loan borrowers. As of April 2016, nearly 40% of Americans who borrowed from the Department of Education are not currently making student loan payments or are behind on monthly payments. In total, more than $200 billion is owed, with 3.6 million borrowers in default, 3 million delinquent, and 3 million having postponed repayment due to economic hardship. These figures represent higher percentages than Americans who have defaulted or stopped paying on revolving home equity loans, credit card debt, and auto loans.

The Department of Education sets limits on how much total funding an individual can receive to pay for higher education expenses. While these amounts are relatively high, students who have no means to pay for tuition, room and board, or books out of pocket often face the need to borrow more than the federal maximum. To meet the growing needs of cash-strapped borrowers, the use of private student loans has increased to just under 20% of all student loans. In some cases, private student loans are used to pay for expenses while a student attends school, and in others, graduates utilize private lenders to refinance federal student loans originally funded by the government. In either case, private student loans have fewer repayment options than federal loans, leading borrowers down a road of inflexibility should financial circumstances change down the road.

The student loan debt crisis continues to be a point of contention among current students, graduates, parents, and lawmakers. Until some stops are put in place to reduce the rapidly increasing cost of attending a college or university or individuals are more motivated to set money aside for their children or grandchildren’s future education, there is no end in sight to impact student loans have on Americans.

*Drew Cloud is an enthusiastic aspiring journalist who recently started his own news outlet, The Student Loan Report. He spends his spare time covering one of his favorite, and most relevant to his finances, topics: student loans.*

]]>

Parts 9-11 dealt with how to **adjust** the withdrawal **amounts** while keeping the **asset allocation fixed** (Guyton-Klinger, VPW, CAPE-based rules, etc.). Prime Harvesting does something completely different: Keep the withdrawal **amount constant**, but use a **dynamic stock/bond asset allocation** to (hopefully) squeeze out some extra withdrawal wiggle room; the Northwest corner in the diagram below. Almost uncharted territory in our series!

Eventually, of course, we like to move to that Northeast corner: Dynamic withdrawals and Dynamic Asset Allocation. But let’s take it one step at a time! Let’s see what this Prime Harvesting is all about.

**Let’s get cranking!**

- This rule was proposed by Michael McClung in his book Living Off Your Money.
- Pick an initial asset allocation, e.g., 60% Stocks, 40% Bonds.
- There is an upper “guardrail” for the stock portfolio. You never withdraw from the stock portfolio until you reach that upper guardrail of equity holdings (and the guardrail is adjusted for CPI inflation). Normally that guardrail is set to 1.2 times the original equity holdings.
- If stocks are at or above 1.2-times their initial level (adjusted for inflation) then sell 20% of stocks and shift into bonds.
- Sell from bonds to fund upcoming withdrawal. If no more bonds are available then sell stocks.
- That’s it. It’s really that easy!

Prime Harvesting has the tendency to first liquidate bonds and let equity gains run for a while before withdrawing. If you have the bad luck of an equity drawdown early during retirement (sequence of return risk!) you avoid selling stocks at the bottom and first live off the bond portfolio until equities recover. Smart move!

You could potentially get lower sustainable withdrawal rates if equities have a very long and sustained bull market (1991-2000) and you start liquidating equities too early by consistently breaching the upper guardrail. But that’s when you least worry about suffering a slightly smaller safe withdrawal rate: 7% or 8%, who cares? PH helps you when you need it the most: when the fixed withdrawal method only sustains a sub-4% withdrawal rate. Of course, the idea isn’t new. Wade Pfau and Kitces have a paper about this exact topic: Why you want a rising (!) equity glide path in retirement.

- The analysis is done annually in the McClung book. We don’t like to withdraw an entire year’s worth of living expenses all at once, so we want our simulations to run monthly rather than annually. The simulations also have to be consistent and comparable with our other simulations!
- The equity rebalancing rule in its proposed form sounds a bit nonsensical. Imagine you start with a million dollar portfolio, $600k in stocks, $400k in bonds. The upper limit for stocks is $720k. Imagine you’re at $719,999. You do nothing. Just one additional dollar and you’d sell a huge pile of $144k worth of stocks and bring the equity holdings to below (!) the initial level. That seems a bit excessive. I found that a more sensible way would be to shift down to $600k (=> reduce by 20% of the
**original**equity weight). Maybe the explanation in the book wasn’t entirely clear and this is what McClung meant. Whatever his intention, this is what I use as the McClung rule. - Even that modified McClung rule creates some pretty nonsensical outcomes, more details below. Instead of selling a lot of equities all at once after breaching the upper guardrail, I also propose a new version, McClung-Smooth, where we sell only enough equities to bring the equity holdings back to the upper guardrail.

Let’s see how the PH methodology would have performed when applied to some of the “trouble-maker” retirement cohorts.

- Monthly Simulations: January 1966 – December 1995 (360 months)
- Pick one initial withdrawal rate (in % of initial portfolio), and adjust the withdrawal amounts by the CPI index regardless of portfolio performance.
- Initial portfolio: 60% stocks, 40% bonds.
- Target capital preservation, so the final portfolio value is the same as the initial, adjusted for inflation after 30 years. Recall that my wife, Mrs. ERN, will be 64 after 30 years of early retirement so I would prefer to preserve capital for at least 30 years.
- The guardrail is 1.2 times the initial value, adjusted for inflation every month.

The asset allocation rules we consider:

**McClung:**after breaching the upper guardrail, sell 20% worth of equities of the original, inflation-adjusted equity holdings, e.g., with a $1,000,000 portfolio shift $120,000 (adjusted for inflation) of the equity portfolio into bonds.**McClung-smooth:**after breaching the upper guardrail sell enough stocks to bring the equity holdings back to the guardrail.**Forced bond liquidation:**Same as above, but with an**infinite**equity guardrail. This has the effect of**never**shifting from stocks to bonds, i.e., we live off the bond portfolio (principal + interest) until bonds are exhausted and then just maintain a 100% stock portfolio.**Glidepath:**We shift to a to a 100% stock, 0% bond portfolio. From a 60/40 portfolio, we steadily converge to a 100/0 portfolio.**Fixed:**We keep a fixed 60/40 allocation.

First, let’s look at the maximum sustainable withdrawal rates that guarantee capital preservation:

- McClung: 3.038%
- McClung-Smooth: 3.071%
- Forced Bond Liquidation: 3.069%
- Glide Path: 3.061%
- Fixed Withdrawal Rate: 2.815%

Nice! With a rising equity glidepath, we beat the low fixed withdrawal rate. But don’t get your hopes up too high. We are talking about a 0.2% difference, $2,000 p.a. in a $1,000,000 portfolio. Not that McClung ever claimed otherwise, but the advantage of the PH method is small. But it is consistent, i.e., we never found a retirement cohort where the fixed SWR was below 4% and the PH method hurt you.

How does the McClung experience look like over time for this cohort? In the chart below we plot the time series of stock and bond levels (top chart, scaled to initial portfolio value of 1.0) and stock and bond portfolio shares as a percent of the overall portfolio. 1966 was a very challenging year. You slowly erode your bonds over about 12 years and then live off the pretty badly decimated stock portfolio. Only when equities recover in the 1980s would you start replenishing the bond portfolio in the late 1980s and early 1990. Notice the four big distinct and discrete jumps in bonds!

The smooth McClung method is exactly identical to the above chart until 1987 because it never hit the upper guardrail for two decades. The shift into bonds is a little bit more gradual. Equities hover around the 0.72 mark for most of the remaining years of the simulation horizon and all the gains above that mark are skimmed off into the bond portfolio. It’s no wonder that the smooth McClung method performs a little bit better than the original McClung method; you keep a higher average equity portfolio during the stock market heydays of the late 1980s and mid-1990s.

Yet another scenario, the forced bond liquidation never moves back into bonds in 1987. Despite the crash in October 1987, you achieve capital preservation with a withdrawal rate not too different from the smooth McClung method.

Working on this research project, I noticed something odd. Below I plot the final value of the portfolio as a function of the withdrawal rate for both the McClung and McClung-Smooth allocation rules. Each tick mark is 0.001% (that’s only $10 annual withdrawal in a $1,000,000 portfolio). For the original McClung, the final value is non-monotone (!) in the withdrawal rate. There are several occasions where the sustainable withdrawal rate moves up (!) when you increase the withdrawal rate. But there are also cases where the final value plummets by a significant amount by merely increasing the initial withdrawal amount by one tick mark. How is that possible? It has to do with the discrete shift out of equities and into bonds as mandated by McClung.

So imagine with a 3.010% withdrawal rate we reach $719,999.99 by a certain month. With a 3.009% withdrawal rate, we’d have reached just a few dollars above $720,000. What if we shifted the $120,000 out of equities, as mandated by McClung, right before another big blockbuster month in equities? It’s possible that we might shift out of equities exactly at the wrong time and end up with a lower final value despite a lower withdrawal rate. But “Natura non facit saltus” which is why we prefer our smooth McClung version (the green line). Thus, as much as I like the spirit of the McClung procedure, the implementation as recommended in his book is unacceptable. You should not get a final value that’s not monotonically decreasing in the withdrawal rate. And, likewise, a change of 0.001% in the initial withdrawal rate making a difference of 5%+ in the final portfolio value is preposterous. This would imply that in a $1m portfolio, a change of $10 in the initial annual withdrawal amount would translate into a $50,000 difference in the final value.

Let’s compare the safe withdrawal rules of other cohorts as well. January 2000 would have been another bad retirement date. To preserve the capital over the next 17 years, a fixed withdrawal amount, adjusted for CPI, would have sustained only a 2.652% initial rate. Again, the McClung-style rules would have outperformed that rate. Quite intriguingly, the glidepath performed the best. Though, the differences are all very small!

Starting retirement at the market peak in October 2007, the fixed withdrawal rate would have supported an initial SWR of just under 4%. McClung again beats this by about 0.20%, but the McClung-Smooth procedure again does better than the regular McClung. Quite intriguingly, the forced bond liquidation and the glidepath beat both of the McClung rules by a very substantial margin.

Let’s look at the chart of equity/bond holdings/percentages for the January 2000 retirement cohort using the McClung-smooth rule. The SWR is only 2.742%. But notice how this retiree never even touched the equity portfolio until 2014. How can a $400k bond portfolio sustain $27,420 p.a. in withdrawals for 14 years and be only half depleted by 2014? That’s a withdrawal rate of 6.855% out of the bond portfolio plus inflation adjustment! We never depleted the fixed income portfolio because bonds did phenomenally well during that period. Yields started at over 6%, then yields went down due to Fed policy (lower target rate, quantitative easing, etc.) and brought large capital gains in bonds. What are the odds we’ll have another bond bull market going forward? Slim to none. Current yields on 10-year Treasury bonds are only slightly above 2%, so average bond returns over the next 14 years can’t possibly match the return of the 2000-2014 period. So the caveat here: Prime Harvesting works best if bonds do well. But that may not be the case over the next few years!

Prime Harvesting is an intuitive method to dynamically shift the stock/bond allocation in retirement. In the past, it would have sustained slightly higher withdrawal rates than the fixed percentage rule when it mattered the most: when stocks did poorly right after retirement. We propose one improvement to this methodology; use a smoother version that avoids selling massive amounts of equities all at once. Letting equities rest at the upper guardrail and skimming only the excess equity wealth above the guardrail seems to be a more sensible approach. It not only avoids the discontinuities and jumps in the final asset value chart above but also tends to afford slightly higher SWRs.

In some of the simulations, we found that just a naive glidepath toward higher equity percentages beats even the more complicated McClung procedure. But that comes at a price: Do people really have the appetite for 100% equities later in retirement?

We are particularly interested in how the Prime Harvesting rule will interact with **dynamic withdrawal amounts**. That’s because in retirement we’d not even be very interested in increasing our withdrawals if the market does well. Instead of buying more consumption (who wants that, we’re all frugal around here, right?) we’d probably prefer to “buy more safety” by derisking the portfolio and shifting into bonds instead. Prime Harvesting would be a good tool to achieve that. But as always, in 2,000 words or so we can only scratch the surface. We are planning more installments of this series, so check this space for more research on this topic!

- Part 1: Introduction
- Part 2: Some more research on
**capital preservation vs. capital depletion** - Part 3: Safe withdrawal rates in different
**equity valuation**regimes - Part 4: The impact of
**Social Security benefits** - Part 5: Changing the
**Cost-of-Living Adjustment**(COLA) assumptions - Part 6: A case study: 2000-2016
- Part 7: A
**DIY withdrawal rate toolbox**(via Google Sheets) - Part 8: A
**Technical appendix** - Part 9:
**Dynamic**withdrawal rates (Guyton-Klinger) - Part 10: Debunking Guyton-Klinger some more
- Part 11: Six criteria to grade dynamic withdrawal rules
- Part 12: Six reasons to be suspicious about the “
**Cash Cushion**“ - Part 13: Dynamic Stock-Bond Allocation through
**Prime Harvesting** - Part 14: Sequence of Return Risk

]]>

Soooooo, where in that $0.5-$5m interval is our net worth? It turns out that our net worth is pretty much in the middle: $2,873,234. Here’s a more detailed breakdown:

**Checking account and credit cards:**Since this is the month-end and right when the paycheck rolls in and right before the mortgage and credit card payments are due we have a lot of cash sitting around. Throughout the month, we try to keep the checking account balance at around $1,000-$1,500.- A
**brokerage account**with Fidelity is worth just under $300k. 100% in low-cost Fidelity index funds! - Our account with Interactive Brokers to implement the
**options trading**strategy we wrote about before holds just under $580k. It’s not exactly an equity investment but most of the risk certainly comes from equity fluctuations. How do we deal with the fact that we hold about 70% of the principal in Muni bond funds and Preferred Shares? We still call that a 90/10 split between equities and bonds because the bonds and bond-like investments are held purely to squeeze some extra yield out of the margin cash. Essentially all of the fluctuations come from futures and options on futures that are all traded on margin. **401k, IRA and Roth/HSA**accounts are just over $900k. All invested in 100% equity index funds.**Deferred compensation**is a plan that’s available at work for voluntarily deferring already vested bonus payments. The actual number is quite a bit larger, about $250k (all invested in equity index ETFs), but we already take into account that we’ll get hit with a large tax bill when I quit my job and cash out the deferred comp plan. Unfortunately, all the income tax will come due at that time and it will be at our high federal and state marginal tax rate. Ouch!- The small
**529 (college savings) account**for Little Miss ERN (3 years old) has about $22k, all invested in an equity index fund. We expect to contribute more over the years but won’t go overboard with the contributions. The objective is to fund a college education at a decent state college, not an all-expenses-paid four-year vacation. I was debating whether to include this account in our net worth. The reason it belongs in the net worth calculations is that, as our blogging friend Green Swan pointed out, it could serve as a last resort liquidity reserve in case our retirement plan doesn’t work out. We hope it doesn’t come to that but if it does… sorry kiddo, you’ll have to rely on student loans in that unlikely event! - We have about $300k in
**private equity**investments. Most of the funds are in**real estate**ventures, specializing in multi-family housing. We spread $270k over three LLCs and I count the combined book values of the funds. All funds have already announced that they see sizable capital gains on the current real estate investments but out of an abundance of caution, we don’t adjust our book value until the gains are actually realized. We also have a small $30k investment in a**venture capital**deal (a long story, more details in another post). If this turns sour it won’t be the end of the world. There were a few bad days in the stock market when we lost more than $30k in a single day, so we consider this investment our “play money” - Our
**home equity**: We take the Zillow estimate of our condo, knock off 7% (5% broker commission plus other fees when we sell our unit next year) and subtract the first mortgage and the home equity line of credit (HELOC). **Other assets**: A hodgepodge of other small accounts, mostly fixed income or fixed-income-style investments.

In case we haven’t mentioned this often enough: We don’t like bonds too much. Equities aren’t cheap either but we just can’t get ourselves to invest more in bonds in the current environment: still very low bond yields, and the prospect of rising yields and more losses in the bond market. But, you may ask, don’t we want diversification? As we wrote before, diversification with bonds is overrated, you don’t want to own bonds when you still have a mortgage and the current equity volatility is so low that we don’t even notice the high equity weight. When was the last time the S&P500 dropped by more than 2%? September 9, 2016!

It’s pretty obvious that we will not be able to retire right now right here in our current city. We have over half a million dollars sitting around in (dead) home equity, though still have a huge mortgage payment every month. But the income we could generate from our investments outside of the retirement accounts would not suffice to finance the mortgage payment and the high living expenses in this mega-metro area.

So, together with some modest capital returns, some more savings and especially the annual bonus to be paid out in early 2018 we hope to grow our net worth to about $3.1m by 3/31/2018. We’ll then sell the condo, move to a cheaper locale, cash out the deferred compensation plan and plan for the following split in our assets (rough estimates, rounded):

- $1m in retirement accounts, not to be touched until later when Mr. ERN turns 60.
- Our income engine in early retirement: $2m in taxable accounts (about $1.35m at Interactive Brokers, $350k in private equity, $300 in public equity). Over time, we will shift some of the funds from the options tradings strategy and into real estate.
- We plan a withdrawal rate of around 3.25-3.50%, based on our research. Make sure you also check out our white paper, posted at the Social Science Research Network (SSRN). It was recently ranked #9 of all recently posted papers!

- We also plan to have $30k in the 529 plan and another $70k in other investments, including a small cash cushion of a few months worth of expenses. This will be a very small cash cushion. Why? Recall our post from a few weeks ago where we wrote about the futility of keeping a large cash cushion to shield against an equity market drop.
- Notably absent from this list: we will most likely not own a home in early retirement, at least initially. We’ll rent for a while and weigh our options about when and where we like to settle down. Maybe we’ll even catch the travel bug like GoCurryCracker or Millenial Revolution for a while.

Wow, I can’t believe I just spilled the beans on our finances! It’s a bell we can’t unring now. I could have done the click bait thing where I dangle “Our net worth is …” in front of you and then after the WordPress “Read More Tag” just write:

“… easier to calculate than our savings rate“

or “… none of your business.”

or “… almost sufficient to retire early.”

or “… the result of careful planning and wise investment decisions.”

But what the heck. If 250 other bloggers can post their net worth, so can we. As we pointed out in our post a few weeks ago, our blogging community seems to be a pretty nice crowd. We’ll keep updating these numbers quarterly from now on, so stay tuned!

]]>

So, here’s our situation: We group our annual compensation into six major categories:

*Side note: we plan our tax withholding so that we come within a few hundred dollars of our actual tax bill. If we were to expect a large tax refund or large tax bill in April we would certainly incorporate that number in the tax component T. *

How should we calculate our savings rate? Here are a few principles about what we should and shouldn’t include:

What **should always** be included in the savings rate calculations:

**Employer matching contributions (S1).**The reason why we’re getting matching benefits for the 401k and the HSA (Health Savings Account) is not because Mr. ERN’s employer is in a charitable mood. Some smart accountants and lawyers figured out a more tax-efficient way of forking over a compensation package that XYZ Inc. deems appropriate for Mr. ERN’s hard work. Whether XYZ Inc. pays it to me and I save it or XYZ Inc. uses the money to match my savings contributions is irrelevant. Money is fungible. So, the entire amount in S1 is included in our savings (but subject to some limitations, see below).**Debt principal payments (in S3).**For us, this is the mortgage principal paydown. From an accounting and economics point of view, there should be no discrimination between building assets and reducing liabilities. We increase our net worth and there is even a “return” on the “savings” in the form of lower future mortgage interest payments. It’s not a very generous return, but it surely beats the 10-Year Treasury yield right now! And of course, the number one reason for including the debt paydown as savings is that the reverse should be even more obvious.**Going further into debt**should be considered**negative savings**. Otherwise, lots of bankrupt folks would argue, “hey, we never had a negative savings rate, we only increased our credit card debt!” How preposterous is that? So paying down the principal of our mortgage is included in S3.

What **should never** be included in the savings rate:

**Mortgage interest.**We want to count our principal paydown as savings, see above, but including the interest portion is a big no-no. For us, the interest payment is essentially the equivalent of rent. We wouldn’t include rent for a house or apartment as savings and likewise, we shouldn’t include the money we pay to the bank to borrow (=”rent”) their money. Same goes for property taxes and homeowners insurance.**Capital income**(interest, dividends, capital gains) from**existing****assets**. This might a contentious issue, so let me explain where I’m coming from. Imagine two individuals, Anne and Ben who each earn $100 in wage income and save $50. They both have a 50% savings rate. But what if Ben has an additional $100 of capital income from retirement savings and it’s all reinvested. It’s probably a bad idea to call that a 150% savings rate. But even if we add the extra income in both the numerator and denominator we get (50+100)/(100+100)=75%. That 75% rate is an accurate estimate of*some*savings rate, for sure. But the question is how sensible and informative is that number? 25 of Ben’s 75% are merely a result of past savings efforts. We probably wouldn’t argue that Ben has a 50% savings rate if she consumed all of his wage income and simply reinvested his capital income: (0+100)/(100+100)=50%. If we want to measure our**savings discipline**and make comparisons between people who are at different stages in their retirement savings accumulation it’s best to set aside the capital income and keep that money behind a firewall! And of course, another reason why I don’t like to include capital income: It’s too volatile for equity-heavy portfolios.

So, keeping those principles in mind, how much do we save? See chart below, which is a breakdown of our annual gross compensation into the six components. We won’t post our actual annual income but this is all scaled; per $100 of total compensation:

- S1: The employer matching is not that high. That’s because more than half of Mr. ERN’s compensation is the annual bonus, which is ineligible for 401k matching. One of the disadvantages of working in finance!
- S2: We slightly over 17% in 401(k), HSA and a plan for voluntary deferrals. The latter is a plan that allows saving a portion of the cash bonus to defer income taxes (though not payroll taxes).
- T: Taxes make up almost one-third of the total compensation. It’s one of the reasons we are planning an early exit from the job market. We are sick and tired of sharing one-third of our hard-earned income on average, and almost 50% at the margin. And this doesn’t even include property and sales taxes!
- D: Deductions for the company health plan, transportation benefits, etc. are only about 1% of the total compensation.
- S3+C: That’s our net income or take-home pay. Only less than half the total compensation. Out of that amount, we consume about 55% and save the rest in after-tax IRAs, taxable savings, mortgage principal reductions, etc.

That’s the easiest savings rate to compute: Divide all the savings by the entire gross compensation:

In our case, that’s 41.24%. Not a very impressive number, but that’s an artifact of the 30%+ average tax rate. We have no illusion of ever generating a 60%+ savings rate based on gross compensation when we pay so much in taxes. It’s still a pretty decent savings performance because in the 3-way split of $100 worth of income we’ll save $41.24, pay $32.52 in taxes and consume $26.24 (actual consumption plus the deductions for healthcare and transportation, which we also consider consumption). Consumption is the lowest and savings the highest share, just like we want it!

Mr. Money Mustache has a classic post to calculate the time you need to reach FIRE as a function of the savings rate. He defines the savings rate as savings “as a percentage of the take-home pay.” What is our take-home pay? I guess it’s our net paycheck, right? If we were to calculate our savings rate as total savings (all the green bars) divided by that take-home pay number we’d reach a pretty impressive number: 90.35%!

How awesome is that? Not very awesome at all because it’s an utterly meaningless number. Specifically, this 90% number is a very bad measure of how frugal we are. Believe me, we’re modestly frugal, but not **that** frugal because this 90% “savings rate” doesn’t imply we consume only 10% of our take-home pay. Do you notice a problem with the formula above? We count the pre-tax savings in the numerator but not in the denominator. The way we calculated the savings rate violates the simple rule that every savings rate formula should satisfy:

If we don’t follow this rule we could get completely non-sensical results. If we had increased our 401k contributions (after-tax, because we max out the pre-tax) and bonus deferral, we could have achieved a 100% (!!!) savings rate, how crazy is that? But simply reshuffling savings should not impact our savings rate.

So, if we’re not careful about calculating our savings rate properly we could easily delude ourselves. Strictly speaking, S3+C is our “take-home pay” but if we look up the 90% savings rate in Mr. Money Mustache’s table and conclude that it should take only under 3 years to reach FIRE we just made a major miscalculation. The 90% savings rate we calculate here doesn’t imply we consume only 10% of our take-home pay. In fact, we consume more than half: 24.97/(24.97+20.68)=55%. Taking the term “take-home pay” in MMM’s post too literally and the formula for how long it takes to reach FIRE is completely wrong.

A more sensible approach to a savings rate based on net income is to simply eliminate the tax component from the denominator but count all of the savings components. In other words, count all savings in both numerator and denominator:

The denominator is not really our take-home pay. But this savings rate is still what we want to use in the FIRE timing calculation a la Mr. Money Mustache or our own post from long time ago. In any case, by that measure, we get to slightly above 60%. Pretty good savings discipline, I would argue, but not crazy-frugal.

One little wrinkle in the calculation above: $1 worth of after-tax savings is worth more than $1 in tax-deferred savings. Physician on FIRE had a nice post on this topic. So, let’s give the various savings components a haircut to account for future tax payments:

- 401k savings: 15%, which is our estimated marginal tax rate on 401k distributions in retirement.
- HSA savings: no haircut! We plan to spend this money on health expenses. Tax-free!
- Voluntary deferrals: if Mr. ERN quits in 2018, the voluntary deferrals would be paid out and taxed at our 2018 marginal tax rate. So we discount the savings by that estimated rate. Ouch!

After applying the haircut to components S1 and S2 and adding a tax component T1 in our breakdown, this is how our total compensation looks like: We just got hit by another $5.51 in taxes for a total of more than $38 per $100 earned. That’s only the average. Marginal taxes are closer to 50%. It’s really time to leave this hamster wheel and retire early!

In any case, if we remove the $5.51 in future taxes from both the numerator and denominator we get a savings rate of just under 58%. Still pretty impressive, still above 50%, but not as high as some of the extremely frugal savers in the FIRE community.

Calculating savings rates is a can of worms. Gross vs. net income makes a difference of 20 percentage points. Fudge the numbers by using our take-home pay instead of after-tax compensation as the denominator and we’d make the not-so-frugal ERN family look super-frugal with a (completely meaningless) 90% savings rate.

]]>

Here are our top six concerns about the cash cushion:

One tripwire to avoid is the following funny accounting mistake: For this example, let’s assume a 3.5% withdrawal rate and a 2% dividend yield. Great! We need only 1.5% to supplement our dividend income. So, a cash cushion of around 7.5% insures against a 5-year equity drawdown, right? Yes, but here’s one pitfall. We have to pick one of these two options:

- Either we assume that we
**eat the dividends**but then we need insurance against a**longer event**because without reinvested dividends the drawdown will take longer. - Or, we assume we
**don’t eat the dividends**and they help us recovering faster from the drawdown. But then we’d need a**bigger cash cushion**because now we need 3.5% in cash for each year of drawdown we want to insure against.

Sorry for pointing out something so trivial, but you’ll be surprised how often we see folks making the mistake of double-counting the dividend yield, i.e., design the annual cash cushion size as withdrawal rate minus yield (i.e., assuming consumption of dividends) but then using the equity drawdown length of the **Total Return** Index, i.e., with dividends reinvested. As we show in the chart below, without reinvesting dividends the drawdowns can be painfully long (top chart). Several *decades long*, so good luck keeping enough cash around for that! When reinvesting dividends, the drawdowns are shorter (bottom chart) but also require more cash cushion per year, i.e., the whole 3.5% in our case, 4% per year for with a more aggressive withdrawal rate. There’s no free lunch!

Another pitfall: The length of the drawdown can be substantially longer than some people assume. We need to reach not just to the previous equity market peak, but that peak **plus inflation **if we assume that we make cost-of-living adjustments in our withdrawals. That doesn’t make much of a difference, you think? Think again! Most drawdowns in the past have lasted substantially longer when taking into account inflation, see chart below.

The bottom panel plots the **real** S&P500, with drawdowns of 36+ months shaded in red (nominal chart in the top panel for comparison). Since 1910, there were seven major drawdowns in the real S&P500 index. Some of them were back to back with a short reprieve in between, and each time it was too short to restock the cash cushion in preparation for the next bear market. So we might as well interpret them as one single event, which means that in the last 107 years there were four major drawdown events:

- 6/1911 – 8/1924:
**13 years and 2 months**comprised of two drawdowns with a short 13 months of reprieve in between. - 8/1929 – 12/1950:
**21 years and 4 months**comprised of two drawdown periods with a short 13 months reprieve in between. - 11/1968 – 1/1985:
**16 years and 2 months**comprised of two drawdown periods with a short 1-month reprieve in between. - 8/2000 – 5/2013:
**12 years and 9 months**

In other words, over the last 107 years, we would have spent 60+ years in major, decade-long drawdown phases. Over the last 50 years, we would have spent almost 29 years in the red. So, pronounced drawdowns that require 10+ years of cash cushions are not the exception but the norm! Multiply the drawdown length above with our desired withdrawal rate (3.5%) and we get completely unrealistic, downright preposterous cash cushions of somewhere between 42% (12 years) to 73.5% (21 years). Ain’t gonna happen!

What if we had consumed the dividends? As we said above, it’s a tradeoff. Consuming the dividends will lower the amount needed per year of drawdown but also create longer drawdown periods. Let’s plot how long the drawdowns last when we plot the real, CPI-adjusted **price return** only (without reinvested dividends), see below:

The most recent drawdown would have lasted 14.5 years (2000 to 2015). During those 14+ years, the cash cushion would have to support the shortfall between a withdrawal rate of 3.5% and the dividend payments. Those dividends were, on average, only 1.5% of the index level in 2000, so we’d have to compensate for the remaining 2% with the cash cushion: 2% times 14.5=29% cash cushion. 36% cash cushion when using a 4% withdrawal rate. Good luck with that!

The 1970s recessions would have been very unpleasant for the cash cushion as well. A 24-year drawdown coupled with a drop in the real dividend (more on that below). We won’t even mention the multi-decade drawdowns between 1900 and 1960 because this cash cushion myth is pretty much busted!

Now assume we have just dug out of a multi-year equity drawdown and thanks to the cash cushion we never had to touch our equity stash. Great job! But now the cash cushion is zero! The equity portfolio has to do double-duty now: It has to generate enough returns to cover the 3.5% withdrawals, 2% or so inflation plus all excess returns to refill the cash cushion. How long will that take? It looks like there have been bull markets long enough to achieve that eventually: 1951-1969 and 1985-2000. But we won’t have any illusion that this is feasible after every single drawdown.

Let’s use the following example wehere we keep 5 years worth of withdrawals on the sidelines, 17.5% of the portfolio. But that means a $1,000,000 portfolio will have only $825,000 in productive assets and $175,000 in zero or even sub-zero expected real return (current return in a money market account or short-term CD is less than the 2% expected inflation rate). So, a $35,000 annual withdrawal is 3.5% of the overall portfolio but 4.24% of the equity portion. That’s getting dangerously high. One alternative would be to keep $1,000,000 in equities and save an **additional** $175k for the cash cushion. But now the effective withdrawal is not really 3.5%. It’s 35,000/1,175,000=2.98%. If the withdrawal rate is so low we might as well invest the entire $1,175,000 in productive assets (80-100% equities) and have a withdrawal rate of just under 3%, which seems pretty darn safe, even for a cranky old pessimist like yours truly, see our previous research on the topic. Specifically, in that post, we showed that a 3% withdrawal rate and a 75-100% equity share had a 100% success probability even for capital preservation, not just capital depletion, over 60 years.

Let’s assume we do withdraw the dividend income. In the past, there have been numerous occasions where dividends have been cut significantly during the recession and/or were eroded by inflation. Professor Shiller has a nice long time series on S&P500 dividends as part of the spreadsheet to construct his CAPE (even though dividends aren’t even used in the CAPE calculation). Don’t let the experience from the 2000s with only short and shallow dividend cuts fool you. There have been some nasty long drawdowns for the real dividend income in the past, see charts below. And those drawdowns in dividend income, you guessed it, coincide with the bear past markets.

Ideally, we’ll just stick with a simple dynamic withdrawal strategy, see Part 11. Rules based on the Shiller CAPE seem to check all our boxes: a) we don’t run out of money, b) muted volatility in withdrawals, and c) moderate drawdowns in consumption levels.

One could also keep a very small cash cushion knowing full well that during a big drawdown it will not last through the bear market. We did a case study in a blog post a while ago that assumed we have a 3.5% withdrawal rate, consume the dividends to stretch out the cushion even longer and keep 12-36 months of expenses in the cash cushion (3.5-10.5%). In each case study, we ran out of money before the market came back. When we started the exercise in December 1997, a little over two years before the market peak with a $1,000,000 portfolio, the equity portfolio without a cash cushion came back to $956k in 2016. With the cash cushion, the different parameterizations would have beat the equity portfolio by $3k to $17k. Not really that much. If we had started the exercise in December 1996 or before, the cash cushion portfolios would have all lagged behind the all-cash portfolio. Opportunity cost!

Another solution would be to use the dynamic withdrawal scheme, called “Prime Harvesting” proposed by a fellow called Michael McClung (see nice summary here). Instead of cash, you hold safe government bonds (10 years maturity) with a higher yield and some diversification potential. Simply draw down the bond portfolio before touching the equity holdings when there’s a drawdown. That’s an interesting and intriguing strategy and we will write more about it in the future.

Some folks suggest to juice up the expected return of that cash cushion with higher yielding assets. That might lower the opportunity cost but also increase the risk. We read suggestions for keeping the “cash” in Preferred Stocks, Junk Bonds and (I am not making this up) REITs. Of course, all of them had nasty drawdowns in the 2008/9 recession. Not much of a help as drawdown protection!

The Cash Cushion approach is really caught between a rock and a hard place. Either the drawdown is so long that you can’t possibly have enough cash to make it through or the drawdown is short enough that the cash cushion likely wouldn’t have made a big difference. We are not convinced!

- Part 1: Introduction
- Part 2: Some more research on
**capital preservation vs. capital depletion** - Part 3: Safe withdrawal rates in different
**equity valuation**regimes - Part 4: The impact of
**Social Security benefits** - Part 5: Changing the
**Cost-of-Living Adjustment**(COLA) assumptions - Part 6: A case study: 2000-2016
- Part 7: A
**DIY withdrawal rate toolbox**(via Google Sheets) - Part 8: A
**Technical appendix** - Part 9:
**Dynamic**withdrawal rates (Guyton-Klinger) - Part 10: Debunking Guyton-Klinger some more
- Part 11: Six criteria to grade dynamic withdrawal rules
- Part 12: Six reasons to be suspicious about the “
**Cash Cushion**“ - Part 13: Dynamic Stock-Bond Allocation through
**Prime Harvesting**

]]>